Driver Drowsiness Measurement Technologies: Current Research, Market Solutions, and Challenges


Significant advances in embedded technologies hold promise to characterize and monitor driver’s state of alertness and detect critical levels of driver drowsiness in real-time. While some enduring solutions have been available as prototypes for a while, many of these technologies are now in the development, validation testing, or even commercialization stages. Several studies have reviewed some available fatigue and/or drowsiness detection solutions. This paper builds on previous studies and aims to provide up-to-date yet complete review on emerging driver drowsiness and alertness monitoring technologies. The contribution of this paper is to identify and review the key objective driver state monitoring technologies namely (i) driving behavioural (vehicle-based), (ii) driver behavioural (video-based), and (iii) driver physiological signals measure based technologies. Each technology is presented with a detailed description of associated detection methods and measuring metrics along with the current research activities and market products in this era. An evaluation of these technologies is also provided in term of intrusiveness, accuracy of detection, and practical use point of view. Therefore, the paper highlights open issues with these emerging systems which need further investigation in the future. We think that this study contribute to a better understanding of sleepiness at the wheel, and will help promote the implementation of accurate crash prevention technologies.

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This work was part of WISSD Project carried out in Heudiasyc Lab. and was co-funded by the French Regional Program (Hauts-de-France), and the European Regional Development Fund through the program FEDER.

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Doudou, M., Bouabdallah, A. & Berge-Cherfaoui, V. Driver Drowsiness Measurement Technologies: Current Research, Market Solutions, and Challenges. Int. J. ITS Res. 18, 297–319 (2020).

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  • Safety
  • Driver drowsiness
  • Vehicle measurement
  • Video sensors
  • Physiological signals